Building portfolio-wide investment insights through AI-powered analysis
The Challenge
One of Scotland's most significant public investment institutions manages a diverse and growing portfolio of early-stage businesses across the country. The investment team faced a familiar challenge: how to build a consistent, real-time picture of portfolio health — identifying where companies were thriving, where risks were emerging, and where targeted support could unlock the most value — without adding to the reporting burden already carried by stretched founding teams. They needed a solution that combined genuine analytical depth with practical, human-led insight.
How We Helped
Engine delivered a fast-paced, 8-week pilot engagement across two integrated workstreams. First, we deployed the Engine Diagnostic Tool with a pilot cohort of five portfolio companies. Each CEO completed a structured self-assessment covering 113 questions across eight critical business dimensions — from leadership and product-market fit through to financial discipline and delivery excellence. Benchmark targets were agreed collaboratively with the investment team, and Engine produced detailed individual reports, conducted one-to-one CEO debriefs, and delivered the first-ever portfolio-level view of maturity, gaps, and cross-cohort strategic themes. In parallel, we built and deployed a proof of concept of the Engine.Assess and Engine.Insights agentic AI platform. Company documents — pitch decks, business plans, financial models — were ingested to create living analytical models of each business. We configured over 40 specialist AI agents to deliver market intelligence, competitive landscape analysis, regulatory and risk assessment, and financial plan examination. The platform was then customised to mirror the institution's own investment process, providing automated checklist evaluation, gap intelligence, and mission alignment scoring at every stage from origination to portfolio monitoring. The combination of proprietary AI platform and experienced consulting team meant we could move from raw data to board-ready insight in weeks, not months.
The Outcome
The pilot received strong feedback from participating CEOs, who described the process as valuable and the platform as clear and easy to engage with. The diagnostic surfaced seven cross-portfolio strategic themes that had not previously been visible at an aggregate level, giving the investment team a new lens through which to prioritise support and allocate resources. The agentic AI platform demonstrated that deep, multi-layered company analysis could be delivered at speed and scale, fundamentally changing what was possible in terms of portfolio intelligence. Off the back of the pilot, the institution is now actively exploring how to move from pilot to full portfolio rollout — combining diagnostic insight, AI-powered analysis, and hands-on advisory support across the full investment lifecycle.
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